Closing the value-based circle in shared decision-making: a digital framework for informing the shared decision-making process through patient reported outcome and experience measures.

Background: The spreading adoption of value-based models of healthcare delivery has incentivized the use of patient-reported outcomes and experience measures (PROMs and PREMs) in clinical practice, with the potential to enrich the decision-making process with patient-reported data. Methods: This perspective article explores PROs and the shared decision-making (SDM) process as components of value-based healthcare. We describe the potential of PROMs and PREMs within the decision-making process and present a digital framework for informing the shared decision-making process using aggregated data from a healthcare system PROMs and PREMs program, including early results from implementation in hospital network in Madrid, Spain. Results: The proposed digital framework incorporates aggregated data from a hospital network PROMs and PREMs program as part of a digital patient decision aid (PDA) for patients with lymphoma. After the first hematologist appointment, participating patients access the PDA to review relevant information about clinical and patient-reported outcomes for each of the possible options, assign a personal order of priority to different outcomes, and then select their preferred course of action. Patients' answers are automatically uploaded to the EHR and discussed with hematologists at the next appointment. After beginning treatment, patients are invited to participate in the network PROMs program; participants' PROMs data are fed back into the PDA, thus "closing the circle" between the decision-making process and patient-reported data collection.During the first 14 months after launching the decision aid in October 2022, of 25 patients diagnosed with follicular lymphoma at the four participating hospitals, 13 patients decided to participate. No significant differences in age or sex were observed between groups. Average SDM Q-9 score for patients filling in the questionnaire (n = 6) was 36.15 of 45 points. Conclusion: Various obstacles toward widespread implementation of SDM exist such as time constraints, lack of motivation, and resistance to change. Support and active engagement from policy makers and healthcare managers is key to overcome hurdles for capturing patient-reported data and carrying out shared decision-making at healthcare system level. Early results of a digital framework for PRO-enriched SDM seem to be beneficial to the decision-making process.

COVID-19 Severity and Survival over Time in Patients with Hematologic Malignancies: A Population-Based Registry Study.

Mortality rates for COVID-19 have declined over time in the general population, but data in patients with hematologic malignancies are contradictory. We identified independent prognostic factors for COVID-19 severity and survival in unvaccinated patients with hematologic malignancies, compared mortality rates over time and versus non-cancer inpatients, and investigated post COVID-19 condition. Data were analyzed from 1166 consecutive, eligible patients with hematologic malignancies from the population-based HEMATO-MADRID registry, Spain, with COVID-19 prior to vaccination roll-out, stratified into early (February-June 2020; n = 769 (66%)) and later (July 2020-February 2021; n = 397 (34%)) cohorts. Propensity-score matched non-cancer patients were identified from the SEMI-COVID registry. A lower proportion of patients were hospitalized in the later waves (54.2%) compared to the earlier (88.6%), OR 0.15, 95%CI 0.11-0.20. The proportion of hospitalized patients admitted to the ICU was higher in the later cohort (103/215, 47.9%) compared with the early cohort (170/681, 25.0%, 2.77; 2.01-3.82). The reduced 30-day mortality between early and later cohorts of non-cancer inpatients (29.6% vs. 12.6%, OR 0.34; 0.22-0.53) was not paralleled in inpatients with hematologic malignancies (32.3% vs. 34.8%, OR 1.12; 0.81-1.5). Among evaluable patients, 27.3% had post COVID-19 condition. These findings will help inform evidence-based preventive and therapeutic strategies for patients with hematologic malignancies and COVID-19 diagnosis.

Impact of hematologic malignancy and type of cancer therapy on COVID-19 severity and mortality: lessons from a large population-based registry study.

BACKGROUND: Patients with cancer have been shown to have a higher risk of clinical severity and mortality compared to non-cancer patients with COVID-19. Patients with hematologic malignancies typically are known to have higher levels of immunosuppression and may develop more severe respiratory viral infections than patients with solid tumors. Data on COVID-19 in patients with hematologic malignancies are limited. Here we characterize disease severity and mortality and evaluate potential prognostic factors for mortality. METHODS: In this population-based registry study, we collected de-identified data on clinical characteristics, treatment and outcomes in adult patients with hematologic malignancies and confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection within the Madrid region of Spain. Our case series included all patients admitted to 22 regional health service hospitals and 5 private healthcare centers between February 28 and May 25, 2020. The primary study outcome was all-cause mortality. We assessed the association between mortality and potential prognostic factors using Cox regression analyses adjusted for age, sex, comorbidities, hematologic malignancy and recent active cancer therapy. RESULTS: Of 833 patients reported, 697 were included in the analyses. Median age was 72 years (IQR 60-79), 413 (60%) patients were male and 479 (69%) and 218 (31%) had lymphoid and myeloid malignancies, respectively. Clinical severity of COVID-19 was severe/critical in 429 (62%) patients. At data cutoff, 230 (33%) patients had died. Age ≥ 60 years (hazard ratios 3.17-10.1 vs < 50 years), > 2 comorbidities (1.41 vs ≤ 2), acute myeloid leukemia (2.22 vs non-Hodgkin lymphoma) and active antineoplastic treatment with monoclonal antibodies (2·02) were associated with increased mortality; conventional chemotherapy showed borderline significance (1.50 vs no active therapy). Conversely, Ph-negative myeloproliferative neoplasms (0.33) and active treatment with hypomethylating agents (0.47) were associated with lower mortality. Overall, 574 (82%) patients received antiviral therapy. Mortality with severe/critical COVID-19 was higher with no therapy vs any antiviral combination therapy (2.20). CONCLUSIONS: In this series of patients with hematologic malignancies and COVID-19, mortality was associated with higher age, more comorbidities, type of hematological malignancy and type of antineoplastic therapy. Further studies and long-term follow-up are required to validate these criteria for risk stratification.